Learn how to detect network anomalies using the Azure machine learning service by running a sample binary classification experiment.
- [Instructor] Let's use Azure Machine Learning Service…to detect network anomalies.…The data set we are using here is KDD Cup 1999.…KDD stands for Knowledge Discovery and Data Mining…and is the name of a conference.…KDD Cup 1999 was a competition…to build a network intrusion detector.…The data set consists of a purest form…of captured network packets with their various features…to be processed by an algorithm.…
In this exercise, we're using a sample experiment…created by the Microsoft Azure Machine Learning team.…The goal of the experiment is…to analyze the KDD Cup 1999 data…and predict which network transaction is malicious.…In our experiment, we consider only two possibilities:…malicious transaction that is an intrusion attempt,…versus normal transaction.…Which is why the experiment is called binary classification.…
Now let's load the experiment…into my Microsoft Machine Learning Studio account.…So I click on Open Studio…and just click on the check mark,…and click on okay.…Now the experiment has been loaded.…
- Network security concepts
- The basic functions of a firewall
- Intrusion detection and prevention systems
- Using network data to improve security
- Using log servers to collect data
- Collecting application data
- Collecting OS data
- Network forensics
- Network security visualization
Skill Level Intermediate
1. Network Security Review
2. Network Data Sources
3. Data Collection
4. Data Analytics
Network forensics2m 25s
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